What do we do?
We have created a methodology that harnesses the power of Big Data, Machine Learning and people to create data ready to be used as knowledge for your AI.
We categorize your data and tag it for you, so that your AI systems can continue improving over time. This process is usually known as training, and like any other type of training, is time consuming and repetitive.
Why we do it?
The main goal of data scientists should be to improve algorithms instead of doing the repetitive but crucial work of training-set-development.
We discovered that many data scientist spend a big amount of their time labeling information instead of improving language algorithms.
We developed a process into a methodology that uses crowdsourcing, Machine Learning and Big Data to label the information for you.
Julio César Amador, CTO
Julio holds a PhD in economics from the University of Essex; his area of expertise is applied machine learning (ML). He has held different research positions, both in the UK and abroad, and is now a research associate at Imperial Business Analytics.
Luis Manuel Pérez Varela, CDO
Luis is an Industrial Designer by the Monterrey Institute of Technology and Higher Education (ITESM) turned web developer and entrepreneur. He co-founded and then sold his first startup, trenddare.com.mx, and is now fully dedicated to pollstr.
Óscar Morales Torres, CEO
Oscar got an got an MBA degree from Hult International Business School in 2013. He met co-founder Julio Amador at ITESM in Mexico City and is now in charge of executing vision and strategy of the company (plus any other number of non-technical tasks inside pollstr).